Epidemiology of Streptococcus pneumoniae and Staphylococcus aureus colonization in healthy Venezuelan children

Streptococcus pneumoniae and Staphylococcus aureus cause significant morbidity and mortality worldwide. We investigated both the colonization and co-colonization characteristics for these pathogens among 250 healthy children from 2 to 5 years of age in Merida, Venezuela, in 2007. The prevalence of S. pneumoniae colonization, S. aureus colonization, and S. pneumoniae–S. aureus co-colonization was 28%, 56%, and 16%, respectively. Pneumococcal serotypes 6B (14%), 19F (12%), 23F (12%), 15 (9%), 6A (8%), 11 (8%), 23A (6%), and 34 (6%) were the most prevalent. Non-respiratory atopy was a risk factor for S. aureus colonization (p = 0.017). Vaccine serotypes were negatively associated with preceding respiratory infection (p = 0.02) and with S. aureus colonization (p = 0.03). We observed a high prevalence of pneumococcal resistance against trimethoprim–sulfamethoxazole (40%), erythromycin (38%), and penicillin (14%). Semi-quantitative measurement of pneumococcal colonization density showed that children with young siblings and low socioeconomic status were more densely colonized (p = 0.02 and p = 0.02, respectively). In contrast, trimethoprim–sulfamethoxazole- and multidrug-resistant-pneumococci colonized children sparsely (p = 0.03 and p = 0.01, respectively). Our data form an important basis to monitor the future impact of pneumococcal vaccination on bacterial colonization, as well as to recommend a rationalized and restrictive antimicrobial use in our community

On generalized surrogate duality in mixed-integer nonlinear programming

The most important ingredient for solving mixed-integer nonlinear programs (MINLPs) to global -optimality with spatial branch and bound is a tight, computationally tractable relaxation. Due to both theoretical and practical considerations, relaxations of MINLPs are usually required to be convex. Nonetheless, current optimization solvers can often successfully handle a moderate presence of nonconvexities, which opens the door for the use of potentially tighter nonconvex relaxations. In this work, we exploit this fact and make use of a nonconvex relaxation obtained via aggregation of constraints: a surrogate relaxation. These relaxations were actively studied for linear integer programs in the 70s and 80s, but they have been scarcely considered since. We revisit these relaxations in an MINLP setting and show the computational benefits and challenges they can have. Additionally, we study a generalization of such relaxation that allows for multiple aggregations simultaneously and present the first algorithm that is capable of computing the best set of aggregations. We propose a multitude of computational enhancements for improving its practical performance and evaluate the algorithm’s ability to generate strong dual bounds through extensive computational experiments

MBSE, PLM, MIP and Robust Optimization for System of Systems Management, Application to SCCOA French Air Defense Program

International audienc

Mediation effects from seemingly unrelated regression test.

<p>Mediation effects from seemingly unrelated regression test.</p